How do I normalise/un-normalise data when loading a model?
How do I convert this to a number between 0-1 without having access to the original car data?


You save the normalisation parameters (typically an offset and a multiplier for each column), and consider that part of the model. Typically you do this when you originally scale training data.

When you want to re-use the model, as well as loading the neural network architecture and weights, you need to load the normalisation parameters in order to re-use those too and scale your inputs.

When tutorials present a self-contained neural network that loads training data, builds a model, then tests that model, all in the same process, then often this step is not shown. However, saving the normalisation data is important, and basically should be considered part of the model, even though it is not directly part of the neural network parameters or hyper-parameters.